第一篇：模擬國際會議PPT

一、基本內(nèi)容

標題頁、目錄頁、章節(jié)內(nèi)容、聲明、參考文獻、致謝

其中，章節(jié)內(nèi)容通常包括主題介紹、實驗或者計算過程、結(jié)果、結(jié)論或總結(jié)

二、PPT制作步驟

1)確定章節(jié)內(nèi)容，對各部分內(nèi)容進行邏輯性分析和重要性排序

2)PPT初步成型

3)PPT詳細設(shè)計

4)檢查完善

三、設(shè)計原則

? 目的明確、思路清晰、邏輯性強

? 文字、表格、圖表合理搭配，并善于使用結(jié)構(gòu)圖

? 簡潔大方、有較好的視覺效果

四、設(shè)計內(nèi)容

? 版式設(shè)計

? 模板設(shè)計

? 配色設(shè)計

? 動畫設(shè)計

? 切換設(shè)計

? 效果設(shè)計

說明：

1)PPT是輔助說明的工具，使表達內(nèi)容達到易于接受、賞心悅目的效果。

2)PPT制作熟能生巧，注意搜集好的設(shè)計和素材，制作時信手拈來。

3)PPT的使用效果與演講者的表達技巧密切相關(guān)，演講者應(yīng)該以飽滿的熱情，盡力將自己

熟知的內(nèi)容分享給觀眾。

第二篇：模擬國際會議演講稿

Recsplorer:Recommendation Algorithms Based on Precedence Mining

1.Introduction Thank you very much, Dr.Li, for your kind introduction.Ladies and gentlemen, Good morning!I am honored to have been invited to speak at this conference.Before I start my speech, let me ask a question.Do you think recomemdations from others are useful for your internet shopping? Thank you.It is obvious that recommendations play an important role in our daily consumption decisions.Today, my topic is about Recommendation Algorithms Based on Precedence Mining.I want to share our interesting research result on recommendation algorithms with you.The content of this presentation is divided into 5 parts: in session 1, I will intruduce the tradictional recommendation and our new strategy;in session 2, I will give the formal definition of Precedence Mining;in session 3, I will talk about the novel recommendation algorithms;experimental result will be showed in session 4;and finally, I will make a conclusion.2.Body Session 1: Introduction The picture on this slide is an instance of recommemdation application on amazon.Recommender systems provide advice on products, movies,web pages, and many other topics, and have become popular in many sites, such as Amazon.Many systems use collaborative filtering methods.The main process of CF is organized as follow: first, identify users similar to target user;second, recommend items based on the similar users.Unfortunately, the order of consumed items is neglect.In our paper, we consider a new recommendation strategy based on precedence patterns.These patterns may encompass user preferences, encode some logical order of options and capture how interests evolve.Precedence mining model estimate the probability of user future consumption based on past behavior.And these probabilities are used to make recommendations.Through our experiment, precedence mining can significantly improve recommendation performance.Futhermore, it does not suffer from the sparsity of ratings problem and exploit patterns across all users, not just similar users.This slide demonstrates the differences between collaborative filtering and precedence mining.Suppose that the scenario is about course selection.Each quarter/semester a student chooses a course, and rates it from 1 to 5.Figure a)shows five transcripts, a transcript means a list of course.U is our target student who need recommendations.Figure b)illustrates how CF work.Assume similar users share at least two common courses and have similar rating, then u3 and u4 are similar to u, and their common course h will be a recommendation to u.Figure c)presents how precedence mining work.For this example, we consider patterns where one course follows another.Suppose patterns occour at least two transcrips are recognized as significant, then(a,d),(e,f)and(g,h)are found out.And d, h, and f are recommendation to u who has taken a, g and e.Now I will a probabilistic framework to solve the precedence mining problems.Our target user has selected course a , we want to compute the probability course x will follow, i.e., Pr[x|a].﹁howerve, what we really need to calculate is Pr[x|aX] rather than Pr[x|a].Because in our context, we are deciding if x is a good recommendation for the target user that has taken a.Thus we know that our target user’s transcript does not have x before a.For instance, the transcript no.5 will be omitted.In more common situation, our target user has taken a list of courses, T = {a,b,c,…} not

﹁just a.Thus, what really need is Pr[x|TX].The question is how to figure out this probability.I will answer it later.Session 2: Precedence Mining We consider a set D of distinct courses.We use lowercase letters(e.g., a, b, …)to refer to courses in D.A transcript T is a sequence of courses, e.g., a-> b-> c-> d.Then the definition of Top-k Recommendation Problem is as follows.Given a set transcripts over D for n users, the extra transcript T of a target user, and a desired number of recommendations k, our goal is to: 1.Assign a score score(x)(between 0 and 1)to every course x ∈ D that reflects how likely it is the target student will be interested in taking x.If x ∈ T , then score(x)= 0.2.Using the score function, select the top k courses to recommend to the target user.To compute scores, we propose to use the following statistics, where x, y ∈ D: f(x): the number of transcripts that contain x.g(x;y): the number of transcripts in which x precedes course y.This slide shows the calculation result of f(x)and g(x,y).For example, from the table, we know that f(a)is 10 and g(a,c)is 3.We propose a precedence mining model to solve the Top-k Recommendation Problem.Here are ﹁some notation: xy, which we have memtioned in session 1, refers to transcript where x occurs without a preceding y;x﹁y refers to transcript where x occurs without y following it.We use quantities f(x)and g(x,y)to compte probabilities that encode the precedence information.For instance, from formular 1 to 7.I would not tell the detail of all formulars.We just pay attention to

﹁formular 5, note that this quantity above is the same as: Pr[x﹁y |yx] which will be used to compute score(x).As we know, the target user usually has taken a list of courses rather than a course, so we need to

﹁extent our probability calculation formulars.For example, suppose T={a,b}, Pr[xT] the probability x occurs without either an a or b preceding it;Pr[x﹁T] the probability x occurs without either an a or b following it.This probability can be calculated exactly.So how to calculate it?

Session 3: Recommendation Algorithms Let’s review session 2.The main goal of the recommendation algorithms is to calculate the score(x), and then select the top k courses based on these scores.Traditional recommendation algorithms compute a recommendation score for a course x in D only based on its frequency of occurence.It does not take into account the courses taken by the target user.Our recommendation algorithms called SingleMC conquer the shortcoming of the traditional ones.It computes the score(x)using the formular 5.The detail is as follows: a student with a transcrip T of taken courses, for the course y ∈ T, if y and x appear together in transcripts satisfies the

﹁threshold θ, then compute the Pr[x﹁y |yx], reflecting the likelihood the student will take course x

﹁and ignoring the effect of the other courses in T;finally the maximum of Pr[x﹁y |yx] is choosen as the score(x).Here is the calculation formular of score(x)of SignleMC.For example, with the higer score, d will be recommended.Another new recommendation algorithm named Joint Probabilities algorithm, JointP for short, is proposed.Unlike SingleMC, JointP takes into account the complete set of courses in a transcript.In formular 12, we cannot compute its quantity exactly, Remember this problem we have mentioned.Our solution is to use approximations.This slide is about the first approximating formular.And this the second approximating formular.The system is courseRand, and data set for experiment contains 7,500 transcripts.This slide shows the new recommendation algoritms with black color and the traditional ones with blue color.The chart on this slide indicates our new recommendation algorithms beat the traditional ones in precision, because the former ones exploit patterns across all users, while the latter ones just use the similar users.The chart on this slide points out our new recommendation algorithms also beat the traditional ones in coverage for the same reason.Session 5: Conclusion and Summary In conclusion, we proposed a novel precedence mining model, developed a probabilistic framework for making recommendations and implemented a suite of recommendation algorithms that use the precedence information.Experimental result shows that our new algorithms perform better than the traditional ones, and our recommendation system can be easily generalized to other scenarios, such as purchases of books, DVDs and electronic equitment.To sum up, first, I introduced the motivation and the outline of work;second, I gave the definition of precedence mining model;third, I described some new recommendation algorithms using precedence information;forth, I showed our experimental results to compare the new algorithms with traditional ones.Finally, I made a conclusion of our work..That’s all.Thank you!Are there any questions?

第三篇：模擬國際會議演講稿

1.Introduction Thank you very much.Mr.Jiao, for your kind introduction.Ladies and gentlemen, Good afternoon!My name is Lijia, came from Harbin Engineering University.I am honored to have been invited to speak at this conference.Before I start my speech, let me ask a question.Do you know what can affect the properties of foam concrete? Do you think how to reinforced the properties of foam concrete？Most of the investigations on foam concrete in the past have been con?ned（被限于）to neat cement paste, cement paste with partial replacement with admixtures and to cement–sand mixes.Today, my topic is about In?uence of ?ller type on the properties of foam concrete.I want to share our interesting research result on reinforced concrete frame with you.The content of this presentation is divided into 4 parts: In section 1, I will introduce what is the foam concrete.In section 2, I will talk about Parameters investigated and mix compositions.In section 3, I will give E?ect of water–solids ratio on design density.And finally, I will make a conclusion.2.Body Section 1: the foam concrete Now, I will introduce the foam concrete.Pre-formed(成型的)foam concrete is manufactured（加工）by adding foam, prepared by aerating（充氣）a foaming agent solution, to cement paste or cement mortar（灰

漿）.The composition（合成物）, physical properties（性能）and uses of foam concrete were discussed in detail（詳細的）by Valore, Short and Kinniburgh, Rudnai and Taylor.Although several investigations have been conducted on the properties of foam concrete, most of them deal with cement–sand mixes, neat cement paste with or without partial replacement（局部替換）using admixtures（摻合料）.Few studies report on the in?uence of ?ller type on the properties of foam concrete.By using ?y ash（粉煤灰）as ?ller(?ne aggregate細骨料)instead of sand, the high volume（體積）utilization（利用）of ?y ash becomes possible可能, thus providing a means of eco-nomic（經(jīng)濟）and safe disposal（處理）of this waste product.Comparison（比較）of strength of air-cured foam concrete made with cement-sand and cement–?y ash for masonry（砌體結(jié)構(gòu)）by Durack and Weiqing show that for products of comparable density（比較密度）, mixes with ?y ash as ?ne aggregate in place of sand gave relatively higher strength.Section 2: Parameters(參數(shù))investigated and mix compositions（組成成分）

So much for the foam concrete, now I will move on to Parameters(參數(shù))investigated and mix compositions.As the experimental programme(實驗程序)was aimed at studying the e?ect of the ?llers on the properties like density（密度）, ?ow behaviour（流動特性）, water absorption（吸水率）and strength of foam concrete, the following mixes

were investigated by keeping the basic ?ller–cement ratio constant（恒定不變）at 1:1 by weight.The foam required for three densities（密度）of foam concrete viz.1000, 1250, 1500 kg/m3 were arrived at as per ASTMC 796-97.In the cement–sand–?y ash mixes 50% of the sand is replaced with ?y ash and in the cement–?y ash mixes all the sand is replaced with ?y ash.Section 3: E?ect of water–solids ratio（水砂比率）on design density That bring me to E?ect of water–solids ratio（水砂比率）on design density.I think this part is the most important in my presentation, I will explain in detail.As the foam is added to the wet foam concrete mix, the consistency（稠度）of the wet mix is very important to get the design density.Fig.2(a)and(b)show the variation of density ratio（密度變化率）(measured fresh density divided（分離）by design density)with water–solids ratio for mixes with di?erent ?ller type for each of the design densities, viz., 1000 and 1500 kg/m3, respectively（分別地）.It is observed that at lower water–solids ratios, i.e., at lower consistency, the density ratio is higher than unity（個體）.The mix is too sti?（嚴格地）to mix properly thus causing the bubbles（氣泡）to break during mixing resulting in increased density.At higher water–solids ratios there is also an increase in density ratio as higher water contents make the slurry（泥漿）too thin to hold the bubbles resulting in segregation（分離）of the foam from the mix along with segregation of the mix itself thus causing

an increase in measured density.Therefore, as shown in Fig.2(a)and(b), a density ratio of unity or nearly unity is achieved only at a particular consistency.This consistency requirement for the mix before adding foam to it can be expressed in terms of water–solids ratio.It is also observed that the water–solids ratio required to obtain a density ratio value of one, depends on the ?ller type.Section 4: Conclusion The conclusions drawn from this study and summarized below are applicable（合適的）to the characteristics of the materials（材料特性）used and the range of parameters（參數(shù)范圍）investigated:(i)the consistency of pre-formed foam concrete mixtures(de?ned as the water–solids ratio for achieving the target（目標）density)mainly depends on the ?ller type, i.e., relatively higher for mixes with ?y ash as ?ller compared to mixes with sand;(ii)the ?ow behaviour mainly depends on the foam volume and as the foam volume increases the ?ow decreases.For a given density, foam concrete with ?y ash as ?ller showed relatively（相當?shù)模﹉igher ?ow values;(iii)for a given density, an increase in ?y ash content of the mix results in increased strength.In comparison（比較）to cement–sand mixes, cement–?y ash mixes showed relatively higher water absorption（吸收）.That’s all.Thank you!Are there any questions?

The picture on this slide is

So much for......, now I will move on to......This slide shows the calculation result

As we know, the target user usually has taken a list of courses rather than a course, so we need to extent our probability calculation formulars.For example, suppose T={a,b}, Pr[x﹁T] the probability x occurs without either an a or b preceding it;Pr[x﹁T] the probability x occurs without either an a or b following it.This probability can be calculated exactly.So how to calculate it?

That bring me to Recommendation Algorithms.I think this part is the most important in my presentation, I will explain in detail.In conclusion, we proposed a novel precedence mining model, developed

To sum up, first, I introduced the motivation and the outline of work;second, I gave the definition of precedence mining model;third, I described some new recommendation algorithms using precedence information;forth, I showed our experimental results to compare the new algorithms with traditional ones.Finally, I made a conclusion of our work..That’s all.Thank you!Are there any questions?

第四篇：英語模擬國際會議講稿

英語模擬國際會議

主持人：王×會議出席人：朱××會議中提問者兩人：董×、趙××休會中途與嘉賓交談兩人：張×、唐×× 會議結(jié)束提問者：余×、龔× 主持人王×：Ladies and Gentleman: May I have your attention please? Our conference will begin in a few minutes.All the presenters are requested to be seated.Let me introduce myself,i am wang yuan from SCNU,it’s a privilege for me to chair this session.Once the ceremony has started,you are refrained from taking pictures, using flashbulbs or leaving your seats.3Q.Distinguished guests, distinguished delegates, ladies and gentlemen, and all the friends:At this special time of wonderful June, in this grand hall of the beautiful city, our respectable guests are here getting together.Academic Seminars of CAS are organized by the Bureau of Personnel and Education of CAS, and held by the CAS research institutes.Now, first of all, please allow me to give our hearty welcome to all of you present, and thank you, for your friendly coming.We feel so proud, and appreciated as well to be the host of the event.For this conference, we are following the agenda here.The meeting is supposed to last for five days，it is the first congress which covers the true sense of psychological education、moral education,basic education and higher education, application education fields.And it to be separated into two parts, to begin with, we’ll invite some representatives from our guests to give lectures about their latest researches and reports on the issue, and then we will have some symposiums.And finally I wish you an unforgettable and prefect experience here.Firstl,i’d like to introduce our first presenter,Professor Jan.She is the author of “cooperation and competition”.for the past six years,JAN has been honored many awards--a Pulitzer Prize winner, a national Medal of the economy and a National book award and so on.Now, please join me in welcoming our guest speaker today---JAN.,whose topic is “cooperation can improve our competitive”.發(fā)言人朱××：

Good morning!Mr.Chairman, your excellencies , fellow colleagues ,Ladies and Gentlemen!Firstly, i would like to thank zhuxiaoli for her gracious introduction.I am very glad to have this opportunity of sharing with you our view on cooperation.My topic of today is“ cooperation can improve our competitive ”.As we all know, competition is a common phenomenon in our society.It occurs in almost every field of our life, such as playing games, doing our study, hunting for jobs.As I stand in here with other Participants ,it’s also a fierce competition.Working hard at something and competing against others can inspire us to push ourselves further than we otherwise might.In other words, competition is required to prompt us to excel and to help us reach our fullest potential.Last of all, competition is seen as an open and fair race where success goes to the swiftest person regardless of his or her social backgrounds.We can say, in this sense, competition stimulates people's interest in work and helps society to go forword.However, as the wave of globalization has come and the development of society, we face more competitions from the outside world.Are we going to face the challenge all by ourselves alone? The answer is clear,Human beings are social beings and no one can exist alone in the society.If you want to play the game well, you have to play with others.You cannot play single-handed and win.You’ll always have to cooperate with your partners, who may make the social ladder for you to climb to the top.From cooperation, you build up trust and understanding, which does good to your future.And also it’s said that we get together to do something larger than one single person, that is to say ,cooperation can turn a small business into a big and strong one.You see,after the cooperation with IBM.Lenovo could challenge the Dell computer company as the world NO.2 PC maker, BenQ and SIMENS mobile, Sony and Ericssons, the two groups of companies are collaborating together to win more market.Everyday, there are over 10 thousand companies annexed because of the crucial competition,but there are collaborating together in order to acquire more competitive ability.From a whole nation’s aspect, all the nations should take the national interest as a common goal.Take China and India for example.India, along with Japan, is a main rival of China in Asia.For the history’s sake, India and China have already competed with each other for a long period of time.With the globalization’s steps getting faster, both China and India realize the importance of cooperation.Now they have already started collaborating in the field of IT and mineral exploitation, and the two countries have benefited a lot.As American previous president Bill Clinton ever said:“There are no forever friends nor rivals, but interest.”So, if situation changes, competition also could turn into cooperation.To sum up, competition and cooperation prevail throughout the world.We should, however, take advantage of the competition as a chance to promote the cooperation and finally be the winner in the competition.we should seek cooperation boardly to improve our competitive.That’s of my speech..Thank you very much, ladies and gentlemen.主持人王×：3Q, Dr.Jan.I think all the participants present here this morning will agree with me that your presentation is very informative and enlightening.Now, do anybody have some questions？

提問1號趙××：（麻煩想個問題，關(guān)于競爭與合作的）提問2號：董×：（麻煩想個問題，關(guān)于競爭與合作的）主持人王×：上半段時間到了，請大家休息10分鐘，10分鐘后會議繼續(xù)。

課間：提問三號張×和唐×一起去喝水，在打水的地方碰到發(fā)言者朱×，然后開始對話。。

張×： 唐×： 朱×： 主持人王×：時間到了，大家安靜就座?，F(xiàn)在有請朱××給大家做一個總結(jié)。朱××：總結(jié)幾句就可以 主持人：還有什么問題嗎？ 提問者3號龔×：（想個問題）提問者4號余×：

（想個問題）

第五篇：國際會議上的ppt怎么做（定稿）

國際會議上的ppt怎么做

之前發(fā)過一次相關(guān)的帖子資源，當時認為幾個比較常見的好書，好資料版內(nèi)很多兄

弟姐妹都有了呢，就只發(fā)了幾個相對不太常見的，可是發(fā)現(xiàn)好像并不是這樣，很多

資料都是大家反復(fù)發(fā)布，總還是有很多人初次見到。我想這可能是“小木蟲”人氣

越來越旺，總有不少新蟲子加入把。

我平時就愛在版里到處搜索有關(guān)“英文科技論文”寫作投稿相關(guān)的資料，電腦了下

載了不少，鑒于以上原因我想把自己看過的覺得好的都一次貼上來，省的大家到處

找，方便大家下載。大家手里已經(jīng)有了的就不用下了，沒有的就看看。

我把有關(guān)資料分成4部分：英文科技論文投稿；如何做國際會議報告；如何進行期刊

投稿；和怎么使用Endnote管理插入文獻四部分來上傳資源。

按照星級說明它的重要性英文科技論文投稿

a 流傳最廣的“strunk and white”著作的關(guān)于如何寫科技論文的好書 elements

of style（中文譯成“文體要素”），這個版內(nèi)以及國外也是流傳最廣的。NO.1五

星級推薦

b 美國科學院院士White Side 寫給自己課題組學生的關(guān)于如何寫作論文的短文，很

短只有3頁，但是一針見血。NO.1五星推薦

c Felicia Brittman寫的中國研究生寫英文文章最常范的200個錯誤總結(jié)，這個我自

己看了好多遍了，里面都是我們常犯的錯誤應(yīng)該如何改正的。五星推薦

d 如何按照EI要求寫作摘要，這個在各學校的EI中國鏈接里都有，但是不一定大家

都注意到了，其實這個摘要太重要了，一定要好好看看，仔細揣摩才行。五星推薦

e 美國印第安納大學 周耀旗教授主動迎合讀者期望，預(yù)先回答專家可能質(zhì)疑。

--美籍華人教授寫的，大家很容易溝通，這是更深層次上對于高手的指點。五星推

薦

fNASA 的 寫英文科技論文的參考工具書--美國航空航天總署的一本關(guān)于如何寫

作的教科書，說實話著我還沒怎么看，三星推薦吧，如果哪位有時間看完了覺得好，上來給大家說一聲。

g英文論文投稿前的經(jīng)典28個細節(jié)檢查；英文文章中標點符號的應(yīng)用及注意事項。

--這兩個之所以發(fā)上來是因為我一向覺得投稿時細節(jié)決定成敗，對于標點，語法等

細節(jié)還有論文排版格式一定要盡量做到和你所投期刊完全一致（還有參考文獻等），因為現(xiàn)在國內(nèi)外期刊稿件都很多，不差你這一篇，你按照期刊要求好好寫作是表

明你的態(tài)度問題。如果我是一個編輯每天處理那么多稿件，來了一個格式亂七八糟的讓我很不爽我直接就扔到垃圾桶里了。

2國際會議報告

國際會議只參加過幾次國內(nèi)的所謂“國際會議”，國外的沒去過，沒有多少經(jīng)驗可

談，但我想主要還是自己的東西新，英語上能說清楚就可以了。但PPT和一些口頭報

告時的套路大家還是應(yīng)該注意一下。

a如何做一個成功的國際會議口頭報告How to make a succesful

presentations五星推薦

b國際學術(shù)會議的英語口語四星推薦

c國際會議報告ppt制作五星推薦期刊投稿

著名的Elsevier數(shù)據(jù)庫 期刊 投稿指南

關(guān)于期刊投稿不同的數(shù)據(jù)庫不同的期刊會有所不同，如果能網(wǎng)上投稿的都會有詳細的要求，大家照著做就可以了。Endnote常見問題解答

Endnote是我用的一個文獻管理工具，寫大論文時比用的，不然上百個文獻如果中間

添加一個沒有endnote或者交叉引用什么的就完蛋了。類似的還有其他的軟件。下面

這個是他的常見問題解答，已經(jīng)譯成中文了。

endnote常見問題解答--已經(jīng)翻譯為中文五星推薦。

[ Last edited by 趙巖hit on 2007-8-23 at 12:44 ]

elements of style1.pdf

? 短文.pdf

? 結(jié).pdf?

相關(guān)回復(fù)：

作者: 趙巖hit發(fā)布日期: 2007-08-23

續(xù)上接著來

? 疑.doc

??

作者: 趙巖hit發(fā)布日期: 2007-08-23

續(xù)3接著來

?

? 英文文章中標點符號的應(yīng)用及注意事項.rar?

作者: 趙巖hit發(fā)布日期: 2007-08-23

國際會議報告部分

其中有一個附件太大了，我在想象辦法

? presentations.pdf?

作者: 趙巖hit發(fā)布日期: 2007-08-23

Endnote使用

期刊投稿也超了，這個就不發(fā)了

?

作者: hjuanzhang發(fā)布日期: 2007-08-23

:D:D:D:D:D

作者: lymcentor發(fā)布日期: 2007-08-23

thank you very much

作者: xuanfeng168發(fā)布日期: 2007-08-23

好人呀，真是太感謝了！

作者: 趙巖hit發(fā)布日期: 2007-08-23

hehe ,xiongdi ,haogeige pingjia a.hehe

作者: dc404發(fā)布日期: 2007-08-23

謝謝！

作者: jiajia++發(fā)布日期: 2007-08-23

:P:P:P:D

作者: guobbaohua發(fā)布日期: 2007-08-23

熱心腸！]

作者: qyw136發(fā)布日期: 2007-08-23

非常好的東西。謝謝

作者: 牛靈妞妞發(fā)布日期: 2007-08-23

:P:P:P:P:PSample Text

作者: franee發(fā)布日期: 2007-08-23

好人啊啊?。?/p>

作者: pluto_918發(fā)布日期: 2007-08-23

不好意思，不曉得如何評價，所以在此就只能以口頭表達謝意了，多謝樓主！:)

作者: wdq19750122發(fā)布日期: 2007-08-23

好東西太感謝了

作者: bracex發(fā)布日期: 2007-08-23

謝謝提供！

作者: yan_yangsc發(fā)布日期: 2007-08-23

歸納的不錯，呵呵。

作者: zwenming發(fā)布日期: 2007-08-23

哈工大的！好帥！感謝你！你是哈工大的驕傲！;);)

作者: sunandshine發(fā)布日期: 2007-08-23

thanks

作者: aishan發(fā)布日期: 2007-08-23

:o:o:rol::rol:

作者: myyouth發(fā)布日期: 2007-08-23

如何能把這些資料做一個合集就好了！專門作成一個文件，里面附帶目錄！

作者: yangjunbo008發(fā)布日期: 2007-08-23 鼓勵一下，向你學習！

作者: lespedeza08發(fā)布日期: 2007-08-23 xie xie！!:P